Englander precision medicine creates big data solution

big data

One of the biggest challenges in precision medicine is what to do with the mountain of data generated from the sequencing of each tumor – how to parse out the relevant information and make it accessible and useful to the physicians making treatment decisions.  Ultimately, such data should be available for a function called Clinical Decision Support.  This function as defined by the Federal Office of the National Coordinator for Health Information Technology is “knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care.”

The Englander Institute for Precision Medicine (IPM) tackled the first hurdle by creating simple-to-read “tumor profiles,” and now it has made another leap by making this data available in Weill Cornell Medicine’s electronic record in a format readily available for Clinical Decision Support.

The technical feat was achieved during the spring, when a cross-institutional team of clinical IT staff and computational biologists from several departments at Weill Cornell Medicine along with Standard Molecular, Inc. successfully linked IPM reports into the Epic electronic medical record (EMR) management system in use by Weill Cornell Physicians in a highly detailed, computer-readable format.

“Integrating a chunk of text and an image of a genomics report in an electronic record has been the existing practice.  This level of integrating rich discretely detailed genomics data into medical records was a longstanding technical challenge, which we have now solved,” said David Artz, MD, Associate Professor of Healthcare Policy and Research (Courtesy) at Weill Cornell and Chief Medical Officer of Standard Molecular.

“This will enable doctors and researchers alike to be able to directly compare lab results with clinical data, which will enhance our ability to truly tailor the care of each patient,” said Dr. Mark Rubin, Director of the Englander Institute for Precision Medicine.

Artz expects the system will be rolled out for doctors’ use in January.  As part of the system, physicians will also be able to set up alerts so they can be notified if a patient’s molecular profile matches specific clinical trial enrollment criteria.

“Since many novel treatments are directed toward molecular targets rather than individual disease subtypes, ready access to this information will be very helpful to clinicians who wish to offer appropriate clinical trials to their patients,” said Dr. John Leonard, the Richard T. Silver Distinguished Professor of Hematology and Medical Oncology.

Successful precision medicine relies on breaking down data silos allowing for broader usage of genetic information in making patient care and treatment decisions, and greater access to additional treatment options through clinical trials.  We have created a system that improves Clinical Decision Support, now the next challenge is bridging the gap for such information to be shared securely with other institutions.

“This project could advance the field of precision medicine beyond Weill Cornell,” Artz said.  “We’ve created a model for how it could be used elsewhere, especially at other institutions that use Epic,” he added.

We are now a step closer to transforming unprecedented amounts of patient data into a teachable resource for the healthcare community to advance precision medicine.